US 12,407,839 B2
Simplifications of cross-component linear model
Yi-wen Chen, San Diego, CA (US); and Xianglin Wang, San Diego, CA (US)
Assigned to BEIJING DAJIA INTERNET INFORMATION TECHNOLOGY CO., LTD., Beijing (CN)
Filed by BEIJING DAJIA INTERNET INFORMATION TECHNOLOGY CO., LTD., Beijing (CN)
Filed on Jun. 21, 2024, as Appl. No. 18/750,699.
Application 18/750,699 is a continuation of application No. 18/212,640, filed on Jun. 21, 2023, granted, now 12,063,377.
Application 18/212,640 is a continuation of application No. 18/126,179, filed on Mar. 24, 2023, granted, now 11,962,789, issued on Apr. 16, 2024.
Application 18/126,179 is a continuation of application No. 17/700,238, filed on Mar. 21, 2022, granted, now 11,632,559, issued on Apr. 18, 2023.
Application 17/700,238 is a continuation of application No. 17/225,955, filed on Apr. 8, 2021, granted, now 11,323,726, issued on May 3, 2022.
Application 17/225,955 is a continuation of application No. PCT/US2019/055208, filed on Oct. 8, 2019.
Claims priority of provisional application 62/742,806, filed on Oct. 8, 2018.
Prior Publication US 2024/0348802 A1, Oct. 17, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. H04N 19/186 (2014.01); H04N 19/105 (2014.01); H04N 19/132 (2014.01); H04N 19/176 (2014.01); H04N 19/30 (2014.01); H04N 19/44 (2014.01); H04N 19/59 (2014.01)
CPC H04N 19/186 (2014.11) [H04N 19/105 (2014.11); H04N 19/132 (2014.11); H04N 19/176 (2014.11); H04N 19/30 (2014.11); H04N 19/44 (2014.11); H04N 19/59 (2014.11)] 15 Claims
OG exemplary drawing
 
1. A method for decoding a video signal, comprising:
reconstructing a luma block corresponding to a chroma block, wherein the luma block is adjacent to a plurality of reconstructed neighboring luma samples, and wherein the chroma block is adjacent to a plurality of reconstructed neighboring chroma samples;
computing a plurality of down-sampled luma samples from the plurality of reconstructed neighboring luma samples;
identifying, from a sub-group of the plurality of computed down-sampled luma samples, two down-sampled maximum luma samples, wherein the two down-sampled maximum luma samples correspond to two first reconstructed chroma samples of the plurality of reconstructed neighboring chroma samples respectively, and the sub-group is composed of a predefined number of the computed down-sampled luma samples among the plurality of computed down-sampled luma samples;
identifying, from the sub-group of the plurality of computed down-sampled luma samples, two down-sampled minimum luma samples, wherein the two down-sampled minimum luma samples correspond to two second reconstructed chroma samples of the plurality of reconstructed neighboring chroma samples respectively;
averaging the two down-sampled maximum luma samples, the two down-sampled minimum luma samples, the two first reconstructed chroma samples, and the two second reconstructed chroma samples, respectively, to obtain an averaged down-sampled maximum luma sample, an averaged down-sampled minimum luma sample, an averaged first reconstructed chroma sample and an averaged second reconstructed chroma sample;
fitting a linear model through the averaged down-sampled maximum luma sample, the averaged down-sampled minimum luma sample, the averaged first reconstructed chroma sample, and the averaged second reconstructed chroma sample;
computing down-sampled luma samples from luma samples of the reconstructed luma block, wherein each down-sampled luma sample corresponds to a chroma sample of the chroma block; and
predicting chroma samples of the chroma block by applying the linear model to the corresponding computed down-sampled luma samples.